Modeling an Individual’s Weekly Change in RG-Score via Novometric Single-Case Analysis

Paul R. Yarnold

Optimal Data Analysis, LLC

Research Gate (RG) weekly summary statistics—including RG-score (the class or “dependent variable”), and number of citations, recommendations, and article views and downloads (the attributes or “independent variables”), were obtained for a single user. Single-case novometric classification tree analysis (CTA) was used to predict RG-score as a function of the number of citations, recommendations, and article views and downloads. Two analyses were conducted: one forced the model to have stable classification in leave-one-out (LOO) jackknife analysis; the second permitted jackknife instability so long as the LOO Type I error rate was p<0.05. A single-attribute model which achieved relatively strong LOO accuracy was identified.

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